Zobrazeno 1 - 10
of 60 320
pro vyhledávání: '"Mateos A."'
Autor:
Galaz, Gaspar, González-López, Jorge, Guzmán, Viviana, Messias, Hugo, Junais, Boissier, Samuel, Epinat, Benoît, Weilbacher, Peter M., Puzia, Thomas, Johnston, Evelyn J., Amram, Philippe, Frayer, David, Blaña, Matías, Howk, J. Christopher, Berg, Michelle, Bustos-Espinoza, Roy, Muñoz-Mateos, Juan Carlos, Cortés, Paulo, García-Appadoo, Diego, Joachimi, Katerine
After over three decades of unsuccessful attempts, we report the first detection of molecular gas emission in Malin 1, the largest spiral galaxy observed to date, and one of the most iconic giant low surface brightness galaxies. Using ALMA, we detect
Externí odkaz:
http://arxiv.org/abs/2410.22230
Autor:
Maria-Moreno, Cristian, Mateos, Ignacio, Pacheco-Ramos, Guillermo, Rivas, Francisco, Cifredo-Chacón, María-Ángeles, Quirós-Olozábal, Ángel, Guerrero-Rodríguez, José-María, Karnesis, Nikolaos
Publikováno v:
IEEE Transactions on Instrumentation and Measurement, vol. 73, pp. 1-11, 2024
In recent years, nanosatellites have revolutionized the space sector due to their significant economic and time-saving advantages. As a result, they have fostered the testing of advanced instruments intended for larger space science missions. The cas
Externí odkaz:
http://arxiv.org/abs/2410.13692
Autor:
Mateos-Ramos, José Miguel, Häger, Christian, Keskin, Musa Furkan, Magoarou, Luc Le, Wymeersch, Henk
Gain-phase impairments (GPIs) affect both communication and sensing in 6G integrated sensing and communication (ISAC). We study the effect of GPIs in a single-input, multiple-output orthogonal frequency-division multiplexing ISAC system and develop a
Externí odkaz:
http://arxiv.org/abs/2410.04176
Autor:
Wasserman, Max, Mateos, Gonzalo
Large-scale latent variable models require expressive continuous distributions that support efficient sampling and low-variance differentiation, achievable through the reparameterization trick. The Kumaraswamy (KS) distribution is both expressive and
Externí odkaz:
http://arxiv.org/abs/2410.00660
Autor:
Chahuara, Hector, Mateos, Gonzalo
Graph signal processing deals with algorithms and signal representations that leverage graph structures for multivariate data analysis. Often said graph topology is not readily available and may be time-varying, hence (dynamic) graph structure learni
Externí odkaz:
http://arxiv.org/abs/2409.12916
Autor:
Ye, Chang, Mateos, Gonzalo
We study a blind deconvolution problem on graphs, which arises in the context of localizing a few sources that diffuse over networks. While the observations are bilinear functions of the unknown graph filter coefficients and sparse input signals, a m
Externí odkaz:
http://arxiv.org/abs/2409.12164
We address the problem of learning the topology of directed acyclic graphs (DAGs) from nodal observations, which adhere to a linear structural equation model. Recent advances framed the combinatorial DAG structure learning task as a continuous optimi
Externí odkaz:
http://arxiv.org/abs/2409.07880
Large deformations of soft materials are customarily associated with strong constitutive and geometrical nonlinearities that originate new modes of fracture. Some isotropic materials can develop strong fracture anisotropy, which manifests as modifica
Externí odkaz:
http://arxiv.org/abs/2407.10501
We propose an elementary proof based on a penalization technique to show the existence and uniqueness of the solution to a system of variational inequalities modelling the friction-based motion of a two-body crawling system. Here for each body, the s
Externí odkaz:
http://arxiv.org/abs/2407.03707
Autor:
Wasserman, Max, Mateos, Gonzalo
Graphs serve as generic tools to encode the underlying relational structure of data. Often this graph is not given, and so the task of inferring it from nodal observations becomes important. Traditional approaches formulate a convex inverse problem w
Externí odkaz:
http://arxiv.org/abs/2406.14786